Some basic statistics functions in F#, including erfc, erfcinv, normcdf, normpdf, norminv, additiveCorrection, multiplicativeCorrection, a Box-Mueller RandomSampler and a unitized type for a Gaussian distribution. Based on Ralf Herbrich's samples at http://blogs.technet.com/b/apg/archive/2008/04/05/trueskill-through-time.aspx
4 people like thisPosted: 5 years ago by Robert Herman
Simple function for commute binomial probabilities. For quick summary about binomial distribution: 1.) There are a fixed number of trials (n). 2.) Each trial has two possible outcomes: success of failure 3.) The probability of success (p) is the same for each trial. 4.) The trials are independent, meaning the outcome of one trial doesn't influence that of any other.
0 people like thisPosted: 2 years ago by Martin Bodocky
Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm. For more information see http://en.wikipedia.org/wiki/DBSCAN. The implementation is based on the pseudocode in the article and the following C# code http://www.c-sharpcorner.com/uploadfile/b942f9/implementing-the-dbscan-algorithm-using-C-Sharp/ The implementation is not very functional but does the job. Added pwd by ignorance, the password is "fssnip" (without quotes)
1 people like thisPosted: 3 years ago by Samuel Bosch
There are better (faster, more efficient) ways to do this, F# numerics library for a start, but this is at least interesting. This snippet uses the polar form of the Box-Muller method to generate Normal- (Gaussian-) distributed random numbers as an infinite sequence. The polar form is more efficient than the basic form as it does not rely on trigonometric function calls, but there are far more efficient alogrithms (read harder to implement) e.g. the Ziggurat method (for a later post).
2 people like thisPosted: 2 years ago by Kevin Roche